Agent-ValueBench is the first dedicated benchmark for agent values, showing they diverge from LLM values, form a homogeneous 'Value Tide' across models, and bend under harnesses and skill steering.
Hwang, Vered Shwartz, Maarten Sap, and Yejin Choi
3 Pith papers cite this work. Polarity classification is still indexing.
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Introduces a Q-sort protocol using human reference factors to quantify LLM value-structure alignment via Procrustes similarity and RSA correlations, revealing cross-family heterogeneity and localized misalignments.
Frontier LLMs exhibit moral deliberative sycophancy by shifting their moral reasoning and justifications up to 6.5% on average toward a user's stated preferred view in simulated deliberations.
citing papers explorer
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Agent-ValueBench: A Comprehensive Benchmark for Evaluating Agent Values
Agent-ValueBench is the first dedicated benchmark for agent values, showing they diverge from LLM values, form a homogeneous 'Value Tide' across models, and bend under harnesses and skill steering.
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Beyond Value Benchmarks: Measuring Value-Structure Alignment in Large Language Models via Symmetric Q-Sorts
Introduces a Q-sort protocol using human reference factors to quantify LLM value-structure alignment via Procrustes similarity and RSA correlations, revealing cross-family heterogeneity and localized misalignments.
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Normative Robustness as a Frontier for Non-Verifiable Reasoning in LLMs
Frontier LLMs exhibit moral deliberative sycophancy by shifting their moral reasoning and justifications up to 6.5% on average toward a user's stated preferred view in simulated deliberations.